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article · Jisuanji fangzhen · 2009

An Adaptive Genetic Algorithm for Blind Source Separation

Huang Shuang-feng

Cited by 0Abstract and details only

Abstract

BSS(Blind Source Separation)and ICA(Independent Component Analysis),which do not require priorknowledge of signals,are widely applied.Independent component analysis(ICA) is a new technique in signal processing.The goal of ICA is to find a separation matrix so that each component of the output signal obtained by transforming the observed multidimensional mixture of data is independent.An adaptive genetic algorithm which combines GA with ICA for blind source separation is proposed in this paper.The convergence and stability of the algorithm are confirmed by comparing with traditional GA.Three sound signals are tested and their validity is confirmed by signal separation test.

Cite this paper

APA 7

Shuang-feng, H. (2009). An Adaptive Genetic Algorithm for Blind Source Separation. Jisuanji fangzhen.

MLA 9

Shuang-feng, Huang. “An Adaptive Genetic Algorithm for Blind Source Separation.” Jisuanji fangzhen, 2009.

Chicago

Shuang-feng, Huang. 2009. “An Adaptive Genetic Algorithm for Blind Source Separation.” Jisuanji fangzhen.

Harvard

Shuang-feng, H. (2009) ‘An Adaptive Genetic Algorithm for Blind Source Separation’, Jisuanji fangzhen.

BibTeX
@article{shuangfeng2009adaptive,
  title = {{An Adaptive Genetic Algorithm for Blind Source Separation}},
  author = {Shuang-feng, Huang},
  journal = {Jisuanji fangzhen},
  year = {2009}
}

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